BOL: Related items

Fulbright-Kalam Postdoctoral Research Scholarships for Indians

Tue, 15 Feb 2022 04:27:22 -0600

These fellowships are designed for Indian faculty and researchers who are in the early stages of their research careers in India. Fulbright-Kalam Climate Fellowships will provide opportunities to talented faculty and researchers to strengthen their research capacities. Postdoctoral fellows will have access to some of the finest resources in their areas of interest and will help build long-term collaborative relationships with U.S. faculty and institutions. These fellowships are for eight to 24 months.

Affiliation
The selected candidate will be affiliated to one U.S. host institution.

USIEF strongly recommends all applicants to identify institutions with which they wish to be affiliated, and to correspond, in advance, with potential host institutions. If the applicant has secured a letter of invitation from a U.S. institution, it should be included as a part of the online application. The letter of invitation should indicate the duration of visit, preferably with dates.

Grant Benefits

These fellowships provide J-1 visa support, a monthly stipend, Accident and Sickness Program for Exchanges per U.S. Government guidelines, round-trip economy class air travel between India and the U.S., a modest settling-in allowance, and a professional allowance.

Subject to availability of funds, a dependent allowance and international travel may be provided for one accompanying eligible dependent provided the dependent is with the grantee in the U.S. for at least 80 per cent of the grant period. Flex grantees are not eligible for dependent benefits.

Eligibility Requirements

In addition to the General Prerequisites:

Applicants must have a Ph.D. degree within the past four years. S/he must have obtained a Ph.D. degree between September 15, 2018 and September 14, 2022. The applicants are required to upload his/her Ph.D. degree certificate/provisional Ph.D. certificate on the online application;
Applicants must have a publication in reputed journals and demonstrate evidence of superior academic and professional achievement. S/he must upload a recent significant publication (copy of paper/article) on the online application (not exceeding 30 pages); and
If applicant is employed, please follow the instructions carefully regarding employer’s endorsement. If applicable, obtain the endorsement from the appropriate administrative authority on the Letter of Support from Home Institution. The employer must indicate that leave will be granted for the fellowship period. The applicant can download the Letter of Support from Home Institution from the USIEF website. Candidates working under government-funded projects are also required to get endorsement from their affiliating institutions in India.

How to Apply

Applications must be submitted online at: https://apply.iie.org/fvsp2023/

The Future of Bioinformatics: Innovations and Opportunities

BioStar — Mon, 20 Jan 2025 12:44:53 -0600

Bioinformatics, the interdisciplinary field that merges biology, computer science, and statistics, has transformed the way we understand biological systems. As we stand at the cusp of a new era in scientific discovery, the future of bioinformatics promises even greater advancements, powered by cutting-edge technologies and a growing understanding of life’s complexities.

1. Big Data and Bioinformatics

The exponential growth in biological data, driven by advancements in sequencing technologies and high-throughput experiments, has made bioinformatics an indispensable tool. By 2030, we anticipate:

Petabyte-Scale Data Management: Enhanced storage solutions and cloud computing platforms will allow researchers to handle the vast amounts of data generated from omics studies, including genomics, transcriptomics, and proteomics.
AI and Machine Learning Integration: Sophisticated algorithms will uncover patterns and relationships in large datasets, enabling predictions about gene function, disease susceptibility, and therapeutic outcomes.

2. Personalized Medicine and Genomics

Bioinformatics will play a pivotal role in tailoring healthcare to individual patients. Key developments include:

Whole-Genome Sequencing in Clinics: The decreasing cost of sequencing will make it routine in medical diagnostics, enabling personalized treatment plans based on an individual’s genetic makeup.
Drug Repurposing and Development: Computational tools will identify potential new uses for existing drugs, accelerating the development of targeted therapies.

3. Advancing Computational Tools

The future will see the development of more user-friendly and powerful bioinformatics tools:

Graph-Based Approaches: Enhanced algorithms for analyzing complex biological networks, such as protein-protein interaction maps.
Visualization Tools: Intuitive software for visualizing multi-dimensional data, enabling researchers to interpret findings more effectively.

4. Synthetic Biology and Systems Biology

Bioinformatics will continue to drive progress in synthetic and systems biology by:

Gene Circuit Design: Leveraging computational models to design and simulate synthetic biological systems.
Understanding Cellular Pathways: Integrating multi-omics data to model cellular processes with unprecedented accuracy.

5. Bioinformatics in Agriculture and Environmental Science

Beyond healthcare, bioinformatics will revolutionize agriculture and environmental conservation:

Crop Improvement: Genomic studies will help develop high-yield, disease-resistant, and climate-resilient crops.
Microbial Ecology: Metagenomics will enhance our understanding of microbial communities, aiding in bioremediation and ecosystem management.

6. Democratization of Bioinformatics

Open-source software and accessible education will broaden participation in bioinformatics research:

Community-Driven Projects: Collaborative platforms like GitHub will continue to foster innovation in tool development.
Education and Training: Online courses and workshops will bridge skill gaps, enabling researchers from diverse backgrounds to contribute.

Challenges and Ethical Considerations

While the future is bright, challenges remain. Data privacy and ethical concerns surrounding genetic information require careful navigation. Furthermore, addressing the digital divide is critical to ensuring equitable access to bioinformatics resources globally.

Conclusion

The future of bioinformatics is boundless, with opportunities to revolutionize our understanding of life and improve human health. As technologies evolve and collaborations flourish, bioinformatics will undoubtedly remain at the forefront of scientific discovery, unlocking the secrets of life one dataset at a time.

Louisiana Biomedical Research Network: Summer Bioinformatics Training Program

eliabrodsky — Wed, 05 Jun 2019 15:30:01 -0500

Louisiana Biomedical Research Network (LBRN) announces registration for it's Summer 2019 Bioinformatics Training Program. The program will be focused on processing, analysis and interpretation of next generation sequecning data for biologists. Learn more:

https://edu.t-bio.info/louisiana-biomedical-research-network-summer-2019-lbrn-bioinformatics-training-program/

Bioinformatics related group

Rahul Agarwal — Sun, 09 Feb 2020 03:17:16 -0600

FaBI emerged from the respective groups of the four founding societies GI (German Informatics Society), DECHEMA (Society for Chemical Engineering and Biotechnology), GBM (Society for Biochemistry and Molecular Biology) and GDCh (German Chemical Society). In fall 2015, the GMDS (German Society for Medical Informatics, Biometry, and Epidemiology) joined FaBI. FaBI represents more than 750 members today and considers itself as a joint representation of interests of bioinformatics research in Germany and as an interlocutor for politics, economy, and society aiming at a strong informatics-based life science research.

Address of the bookmark: https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html

Research Rabbit

LEGE — Fri, 07 Apr 2023 12:01:33 -0500

You’re determined students, passionate teachers, and inspired creators of everything we know! Yet, all the researchers we spoke with over the past year uncovered the same reality:

Despite the degrees you’ve earned, the effort and passion you put in every day, the sacrifices you make – academia burdens you with tons of stressors. Financial, psychological, physical, and more.

We’re an unconventional team with backgrounds in various fields – both inside and outside of academia. And through our lens, it’s clear that academia deeply undervalues and underserves its very own community!

It’s time to reimagine research.

Address of the bookmark: https://researchrabbitapp.com/

Comparison of Short Read De Novo Alignment Algorithms

Rahul Agarwal — Wed, 21 Aug 2013 07:56:01 -0500

Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.

Title: Comparison of Short Read De Novo Alignment Algorithms

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

coursera genome assembly tutorial

Jit — Sat, 25 Nov 2017 08:57:25 -0600

Solutions to Coursera Genome Sequencing (Bioinformatics II)

Address of the bookmark: https://github.com/iansealy/coursera-assembly

COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly

Jit — Wed, 06 Dec 2017 02:08:14 -0600

An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.

Address of the bookmark: ftp://ftp.genomics.org.cn/pub/cope

3d-dna: 3D de novo assembly (3D DNA) pipeline

Jit — Thu, 28 Dec 2017 10:09:37 -0600

This code is designed to enable anyone to reproduce the Hs2-HiC and the AaegL4 genomes reported in: Dudchenko et al., De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science, 2017.

Unless otherwise noted, all terminology below is consistent with this paper, and all references to figures and tables in this readme refer to this paper. Specifically, some of the terminology used below is outlined in Figure S2. The assembly procedure is described in detail in the Supporting Online Materials, specifically in the section labelled “Pipeline description”.

In addition, the pipeline uses tools and methods from Juicer (Durand & Shamim et al., Cell Systems, 2016) and Juicebox (Durand & Robinson et al., Cell Systems, 2016), as well as additional dependencies noted below.

Feel free to post your questions and comments at: http://www.aidenlab.org/forum.html

http://aidenlab.org/documentation.html

Address of the bookmark: https://github.com/theaidenlab/3d-dna

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Rahul Nayak — Tue, 05 Jun 2018 09:57:11 -0500

PERGA - Paired End Reads Guided Assembler PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct contig, PERGA uses paired-end reads and different read overlap sizes from O ≥ Omax to Omin to resolve the gaps and branches. Moreover, by constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. PERGA will try to extend the contigs by all feasible nucleotides and determine if these multiple extensions due to sequencing errors or repeats by using looking ahead technology, and it also try to separate the different repeats of nearby genomic regions to make the assembly result more longer and accurate. The simulated E.coli paired-end reads data are generated using GemSim (KE McElroy, F Luciani, T Thomas. Gemsim: General, Error-Model Based Simulator of Next-Generation Sequencing Data. BMC Genomics 2012, 13:74), with coverage 50x, 60x, 100x, read lengths 100-bp, and can be downloaded from https://github.com/zhuxiao/data_PERGA.

Address of the bookmark: https://github.com/hitbio/PERGA